1. Joint Modeling
1.1 Trace plots for convergence check
The current MCMC setting is:
- 4000000 iteration;
- 3000000 burn-in;
- 1000 thinning.
1.2 Gelman and Rubin’s convergence check
## Potential scale reduction factors:
##
## Point est. Upper C.I.
## HDevsum 1.00 1.00
## LDevsum 1.00 1.00
## dh0 1.02 1.07
## dh1 1.01 1.05
## dh2 1.00 1.00
## dl0 1.03 1.13
## dl1 1.02 1.05
## dl2 1.00 1.00
## dl3 1.02 1.07
##
## Multivariate psrf
##
## 1.02
1.3 ACF Plots
Here we plotted ACF plots for the following variables:
- Total deviance;
- Variables that didn’t pass the convergence check.
1.4 WAIC results
| LevelH | LevelL | |
|---|---|---|
| DIC | 1235.19486 | 24473.963 |
| DIC3 | 1168.53361 | 21058.789 |
| PWAIC | 50.43742 | 1182.659 |
| WAIC | 1202.36863 | 21573.665 |
2. Separate Modeling of High-Level
2.1 Trace plots for convergence check
The current MCMC setting is:
- 4000000 iteration;
- 3000000 burn-in;
- 1000 thinning.
2.2 Gelman and Rubin’s convergence check
## Potential scale reduction factors:
##
## Point est. Upper C.I.
## HDevsum 1.00 1.01
## dh0 1.02 1.03
## dh1 1.00 1.01
## dh2 1.01 1.01
##
## Multivariate psrf
##
## 1
2.3 ACF Plots
Here we plotted ACF plots for the following variables:
- Total deviance;
- Variables that didn’t pass the convergence check.
2.4 WAIC results
| H2 | |
|---|---|
| DIC | 1370.66057 |
| DIC3 | 1237.49235 |
| PWAIC | 87.16183 |
| WAIC | 1304.39421 |
3. Separate Modeling for Low-level
3.1 Trace plots for convergence check
The current MCMC setting is:
- 4000000 iteration;
- 3000000 burn-in;
- 1000 thinning.
3.2 Gelman and Rubin’s convergence check
## Potential scale reduction factors:
##
## Point est. Upper C.I.
## LDevsum 1.00 1.00
## dl0 1.01 1.05
## dl1 1.01 1.04
## dl2 1.00 1.01
## dl3 1.03 1.09
##
## Multivariate psrf
##
## 1.01
3.3 ACF Plots
Here we plotted ACF plots for the following variables:
- Total deviance;
- Variables that didn’t pass the convergence check.
3.4 WAIC results
| L7 | |
|---|---|
| DIC | 24041.817 |
| DIC3 | 20963.360 |
| PWAIC | 1181.658 |
| WAIC | 21476.015 |